@article{ByrdGilbNoce00,
 author         = {R. H. Byrd and J.-Ch. Gilbert and J. Nocedal},
 title          = {A Trust Region Method Based on Interior Point Techniques
                   for Nonlinear Programming},
 journal        = MP,
 volume         = {89}, number = {1}, pages = {149-185}, year = 2000}
 abstract       = {An algorithm for minimizing a nonlinear function subject to
                   nonlinear equality and inequality constraints is described.
                   It can be seen as an extension of primal interior point
                   methods to non-convex optimization. The new algorithm
                   applies sequential quadratic programming techniques to a
                   sequence of barrier problems, and uses trust regions to
                   ensure the robustness of the iteration and to allow the
                   direct use of second order derivatives. An analysis of the
                   convergence of the new method is presented.},
 summary        = {An algorithm for minimizing a nonlinear function subject to
                   nonlinear equality and inequality constraints is described.
                   It can be seen as an extension of primal interior-point
                   methods to non-convex optimization. The algorithm applies
                   SQP techniques to a sequence of barrier problems, and uses
                   trust regions to ensure the robustness of the iteration and
                   to allow the direct use of second order derivatives. A
                   convergence analysis is presented.}}